During transcoding of quantized digital signals, such as a video signal, for example, a digital input signal is converted into a new digital output signal. A method for transcoding can be used to adapt the input signal for different transmission requirements and/or various terminal device functionalities. In so doing, the adaptation of a data rate of the input signal can be carried out by new quantization. More complex transcoding methods modify further parameters, such as a refresh rate or a screen resolution in cases of transcoding a video signal.
With the aid of FIG. 1, a coding chain with transcoding of digital signals is described in more detail. An uncoded image signal features a plurality of brightness and color values which are edited in the spectral range, for example. These uncoded values are labeled as uncoded data values X0.
An uncoded data value X0, i.e. an input data value X0, is coded in a first coder C1 to a first intermediate data value X1. The coding takes place with the aid of a first quantization Q1. The first intermediate data value X1 is decoded into the second intermediate data value X2 using the first decoder D1. In this connection, a first inverse quantization IQ1 is carried out. The second intermediate data value X2 corresponds to the uncoded data value X0 apart from a quantization error. This second intermediate data value X2 is coded into a third intermediate data value X3 with the aid of a second coder C2. The second coder C2 uses a second quantizer C2 for coding. Subsequently, the third intermediate data value X3 is decoded into a final data value X4 using a second decoder D2. The decoding takes place in the second decoder D2 by the application of a second inverse quantization IQ2. The final data value X4 corresponds to the uncoded data value X0 apart from a quantization error, whereby this quantization error is caused both by the first quantization Q1 or first inverse quantization IQ1 and by the second quantization Q2 or second inverse quantization IQ2.
If, for example, a video distribution service is observed, then for a plurality of video images, having a plurality of uncoded data values X0, a plurality of first intermediate data values X1 are generated with the aid of the first coder. These first intermediate data values X1 are, for example, filed on a hard disk for later organized transmission to a terminal device. In order to transfer the video images to a terminal device in the suitable form, e.g. with a low data rate, the first intermediate data values X1 can be decoded into the second intermediate data values X2 with the aid of the first decoder. Subsequently, the second intermediate data values X2 are coded into the third intermediate data values X3 using the second coder, and can subsequently be transmitted to the desired terminal device in this form. The terminal device receives the third intermediate data values X3, decodes these with the aid of the second decoder D2 and displays the decoded end data values X4 on a screen, for example. In FIG. 1 a transcoding device TR is described with the aid of the first decoder and the second coder which transcoding device, for example, conducts a reduction of the data rate in the form of a code conversion of the first intermediate data values X1 (=input signal) into the third intermediate data value X3 (=output signal).
Digital signals, such as digital video signals, are coded or compressed for transfer with the aid of known coding standards, for example MPEG4 (MPEG—Motion Picture Expert Group) or H.264. These coding standards or video coding methods break the video signal down into blocks and introduce a motion compensation for predictive coding. The individual blocks are thereby broken down into spectral components by a mathematical map. For better compression the spectral components are quantized, such that components are removed from the signal which are not or only insignificantly recognizable for an observer. These removed components are also no longer accessible or reproducible within the transcoder.
The removal of signal components leads to additional quantization losses or quantization errors arising through a high quantizer level while carrying out an additional new quantization within the transcoder with the aid of the second quantization Q2. This means that, through the use of the first and second quantization, higher quantization errors arise than with the use of an individual quantizer. A loss in quality arising through the transcoding due to the new quantization leads to a visible deterioration of the image quality.
In FIG. 2, an image quality in PSNR (PSNR—Peak Signal to Noise Ratio) can be seen in exemplary form from the quantization level using one and two quantizations when used in a video coding method. The quantization level indicates a number of amplitudes of data values which are summarized within a quantization interval to a reconstruction value. For example, with a quantization level of 15 the amplitudes from 0 to 14 or from 15 to 29 etc. are each summarized to a reconstruction value, e.g. 7, 23 etc. The larger the quantization level, the stronger the compression by the quantization. The curve marked with squares is a first reference curve R1 and describes the image quality when using an individual quantizer, whereby quantization is performed with the quantization level indicated in FIG. 1. A second reference curve R2, marked with circles, shows the image quality with the use of two quantization levels according to FIG. 1 connected to each other in series, whereby quantization takes place in the first quantization Q1 with a first quantization level of 12 and in the second quantization Q2 with the quantization level indicated in FIG. 2, e.g. 20. It can thereby clearly be seen that the second reference curve lies underneath the first reference curve. So the difference in image quality PSNR at a quantization level of 20 is around 2 dB (dB—decibels). This means that with the use of more than one quantization the image quality is significantly reduced as compared to that with the use of an individual quantization.
Today, known video transcoders typically consist of the series connection of a decoder and a coder. A good overview can be gained from A. Vetro et al., “Video Transcoding Architectures and Techniques: An Overview”, IEEE Sig. Proc. Mag., March 2003, pp. 18-29. The decoder decodes the input signal either completely or up to a specific level, such that at least the amplitudes of the spectral coefficients from the quantized values are calculated in order to be able subsequently to conduct a new quantization. For the sake of a reduction in complexity, both these decoded data values and peripheral information, like for example prediction modes and/or motion vectors, can be assigned to the second coder. In the second coder the rate adaptation by new quantization can be conducted with a higher quantization level than in the first quantization Q1. In O. H. Werner, “Generic Quantiser for Transcoding Hybrid Video”, Proc. Pict. Cod. Symp. (PCS), 1997, a method is presented which adjusts the quantization in terms of the coefficients of the input data values and the additionally developed drift. Methods are known from P. A. Assuncao et al., “Optimal Transcoding of Compressed Video”, IEEE Proc. Int. Conf. Image Proc. (ICIP), Vol. 1., 1997, pp. 739-742, and W.-N. Lie et al., “Rate-Distortion Optimized DCT-Domain Video Transcoder for Bit-Rate Reduction of MPEG Video; IEEE, Proc. Int. Conf. Aud. Sp. and Sig. Proc. (ICASSP), Vol. V., 2004, pp. 969-972, which use a Lagrange approach, in which the quantization is chosen in such a way that the distortion is minimal in terms of a predetermined rate, for the adjustment of the new quantization. We will, however, not go into the choice of a new reconstruction value in this connection.